Publikationen

Shah, G.; Thierbach, K.; Schmid, B.; Waschke, J.; Reade, A.; Hlawitschka, M.; Roeder, I.; Scherf, N.; Huisken, J.: Multi-scale imaging and analysis identify pan-embryo cell dynamics of germlayer formation in zebrafish. Nature Communications 10, 5753 (2019)

Burek, P.; Scherf, N.; Herre, H.: Ontology patterns for the representation of quality changes of cells in time. Journal of Biomedical Semantics 10, 16 (2019)

Burek, P.; Scherf, N.; Herre, H.: A pattern-based approach to a cell tracking ontology. Procedia Computer Science 159, S. 784 - 793 (2019)

De Back , W.; Seurig, S.; Wagner, S.; Marre, B.; Roeder, I.; Scherf, N.: Forensic age estimation with Bayesian convolutional neural networks based on panoramic dental X-ray imaging. In: Proceedings of the 2019 International Conference on Medical Imaging with Deep Learning (MIDL). (2019)

Kloenne, M.; Niehaus, S.; Lampe, L.; Merola, A.; Reinelt, J.; Scherf, N.: Convolutional neural network stacking for medical image segmentation in CT scans. In: 2019 Kidney Tumor Segmentation Challenge. MICCAI 2019, Shenzhen, China, 13. Oktober 2019 - 19. Oktober 2019. University of Minnesota Libraries Publishing, Minneapolis, MN (2019)

Podranski, K.; Zhang, R.; Thierbach, K.; Thieleking, R.; Witte, A. V.; Villringer, A.; Weiskopf, N.; Scherf, N.: Detecting fat artifacts in diffusion MRI with deep learning. 9th IMPRS NeuroCom Summer School, Leipzig, Germany (2019)

Kloenne, M.; Niehaus, S.; Lampe, L.; Merola, A.; Reinelt, J.; Scherf, N.: A framework for CT image segmentation inspired by the clinical environment. arXiv (2019)